Triple
T6102791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seattle grunge movement |
E136041
|
entity |
| Predicate | fashionCharacteristic |
P68143
|
FINISHED |
| Object | flannel shirts |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: flannel shirts | Statement: [Seattle grunge movement, fashionCharacteristic, flannel shirts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fashionCharacteristic Context triple: [Seattle grunge movement, fashionCharacteristic, flannel shirts]
-
A.
dressFeature
Indicates that a dress possesses or is characterized by a particular feature, attribute, or design element.
-
B.
coatCharacteristic
Indicates that one entity has a particular property, feature, or quality that characterizes its outer covering or surface.
-
C.
fashionStyle
Indicates the characteristic way in which an entity dresses or presents themselves in terms of clothing and appearance.
-
D.
fashionLabel
Indicates that an entity is a fashion brand or label associated with the design, production, or marketing of clothing or accessories.
-
E.
neckCharacteristic
Indicates that an entity has a specific attribute, feature, or quality related to its neck.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c0087dee9881909e3655be88208c01 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05b3dbc6c8190b9e3d81e6ca9eeb8 |
completed | March 22, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69c049f5ac988190b62ba565153aaa35 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8e3f2c8190be459ca02f9b315a |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:13 p.m.